1. Cross-References to Related Applications
This application claims priority under 35 USC § 119 to Korean Patent Application No. 2004-83401, filed on Oct. 19, 2004, the contents of which are herein incorporated by reference in its entirety for all purposes.
2. Field of the Invention
The present invention relates to a method of inspecting defects and an apparatus for performing the same. More particularly, the present invention relates to a method of inspecting defects that is capable of detecting the defects on a precision object such as a semiconductor substrate and then classifying the defects, and an apparatus for performing the method.
3. Description of the Prior Art
Continued improvements in semiconductor design and manufacturing result in devices having ever increasing integration and capacity. Such devices require extremely accurate thin layer patterns to be formed on the semiconductor substrate, and such accuracy is determined by inspecting the resulting pattern formed. For example, after a pattern is formed on a semiconductor substrate, defects such as particles or micro-scratches may be generated on the pattern. Planarization of the pattern by a chemical mechanical polishing (CMP) process may also generate the above-mentioned defects on the pattern.
As both the size of the semiconductor substrates increase and devices using such substrates become more highly integrated, increasing numbers of inspection regions are required to be tested on a single semiconductor wafer. In the past, tens of inspection regions would be set on a single semiconductor substrate, and tens of defects on the semiconductor substrate detected. With increased integration, however, hundreds to thousands of inspection regions are set on a single semiconductor substrate resulting in hundreds to thousands of defects detected on the semiconductor substrate. The increased number of required inspections has resulted in a skyrocketing time to complete the inspection of the semiconductor devices.
FIG. 1 is a flow chart illustrating a conventional method of inspecting defects.
Referring to FIG. 1, in step S11, a semiconductor substrate is scanned using a defect inspection tool to obtain information about the semiconductor substrate. In step S13, the information is converted into a digital signal and, in step S15, the digital signal is stored in a server. In step S17, defects on the semiconductor substrate are detected and classified based on the digital signal. In step S19, the number of the defects is accumulated to determine whether it is beyond a predetermined allowable number or, in the alternative, whether critical defects are recognized on the semiconductor substrate.
When the number of the defects is beyond the allowable number or critical defects are found on the semiconductor substrate, in step S21, the semiconductor substrate is manually/visually inspected with the help of a reviewing tool such as a microscope, a scanning electron microscope (SEM), etc., to recognize the configuration, shape, and kind of the defect. Critical defects are recognized during this manual inspection process.
Whether the defects are found during the reviewing steps to be normal or critical determine whether following process steps are carried out. When the defects are determined to be normal, in step S25, the subsequent process is carried out. On the other hand, when the defects are determined to be abnormal, in step S27, the subsequent process is not performed on the semiconductor substrate. Instead, the process is suspended and the apparatus used for a preceding process (and being the potential cause of the defect formation) is then repaired as required.
Critical defects are primarily recognized using a defect-classifying program. The defect-classifying program classifies the detected defects based on parameters such as a contrast, an intensity, a size, etc. Here, the parameters correspond to reference values for processing the information of the detected defects.
FIG. 2 is a graph illustrating a typical inspection result obtained using the conventional method. In FIG. 2, a vertical axis represents the contrast and a horizontal axis represents the intensity. Values of the contrast and the intensity in FIG. 2 are expressed as conversion units.
As shown in FIG. 2, defects having diverse contrasts and intensities are shown to exist on the semiconductor substrate. It has been found, however, that defects with diverse contrasts and intensities may actually be of a similar type and that those defects with similar contrasts and intensities may in fact be quite different types of defects—a fact that cannot be determined from a simple inspection of the conventional contrast/intensity plot as shown in FIG. 2. That is, defects having the above-mentioned conditions are not adequately distinguished from each other.
It is particularly important to accurately classify the defects by accurately distinguishing between intrinsic signals of the defects and background signals of a region where the defects exist. Here, a standard for distinguishing between the intrinsic signals of the defects and the background signals of the region corresponds to a parameter. The parameter for distinguishing the intrinsic signals of the defects varies in accordance with kinds of the background signals. For example, to accurately inspect particles on a cell region of a semiconductor substrate, a contrast is an optimal parameter. Also, to accurately inspect particles on a peripheral region of the semiconductor substrate, an intensity is an optimal parameter.
According to the conventional method, since the defects detected from entire regions of a semiconductor substrate are classified based on the same parameters, the conventional defect classification has a very low accuracy. Thus, defect inspection under the conventional method requires a further manual inspection to determine whether the critical defects found would be of the type that would influence subsequent processing or operation. Accordingly, the time required to conduct inspections of the devices increases thus also increasing a cost for manufacturing the semiconductor device.
To overcome the above-mentioned problems, a method of classifying defects is disclosed in Japanese Patent Laid Open Publication No. 2004-148031. In the method of classifying defects, characteristic parameters by densities of patterns on each region of a semiconductor substrate are set. Defects in regions that have densities substantially similar to each other are then classified as a same defect. An image of the semiconductor substrate is obtained using an SEM, a typically time intensive procedure. The defects in the regions having the similar densities are detected from the image and are then classified as the same defect based on the characteristic parameters. That is, since the SEM is used in the conventional method, efficiency for detecting defects is very low. And although the regions have similar densities, the regions may in fact have different kinds defects so that the defect classification is relatively inaccurate. Regions having the similar densities but different defect types may have different background signals. As a result, parameters for inspecting the defects in the regions may be different from each other. Further, to effectively inspect the defect, different parameters may be employed in the inspection process in accordance with the kinds of the defects in the regions having the similar densities. Thus, a reviewing of the defects is required in the conventional method resulting in the original problem.
Accordingly, the need remains for an inspection tool and method for more accurately and quickly detecting and classifying defects that occur on semiconductor devices during manufacturing.